{"uid":"cap_C1XSZIGw5pl5ZdZiHFlQQ","slug":"cortexcloud-rerank-ae429ee8","name":"CortexCloud Rerank","description":"Result reranking by relevance (Cohere primary, Jina fallback). x402-paid, USDC on Base.","url":"https://api.cortexcloud.org/v1/ml/rerank","method":"GET","headers":{},"bodySchema":{"properties":{"input":{"properties":{"body":{"type":"object","properties":{}}}},"output":{"properties":{"example":{}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.006","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.006/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.006","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.006","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_eAPULGWJNbAICmGM_a6fc","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.006","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Reranks a list of documents or passages by relevance to a query using Cohere (primary) with Jina as fallback, paid per call in USDC via x402.","exampleAgentPrompt":"Rerank these 10 retrieved passages by how relevant they are to the question 'What are the side effects of ibuprofen?' and return them sorted with relevance scores — pay the per-call fee in USDC.","exampleUseCases":[{"title":"RAG pipeline context improvement","prompt":"I have 20 chunks retrieved from my document store for the query 'how does compound interest work' — can you rerank them by relevance so I only feed the top 5 most relevant ones to the LLM?"},{"title":"Search results reordering","prompt":"I ran a keyword search and got back 15 product descriptions for 'wireless noise-cancelling headphones' — rerank them so the most semantically relevant ones appear first."},{"title":"QA candidate passage selection","prompt":"Here are 12 passages extracted from medical literature — rerank them by relevance to the question 'What are the recommended treatments for type 2 diabetes?' so I can pick the best ones to cite."}],"resultDescription":"An ordered list of the input documents re-sorted by relevance score to the query, with each document assigned a numeric relevance score. The highest-scoring, most semantically relevant documents appear first.","failureModes":["Payment not included or insufficient USDC on Base — returns 402 Payment Required","Upstream Cohere API unavailable and Jina fallback also fails — returns 5xx error","Empty or malformed document list — returns 400 Bad Request","Query string missing — reranking cannot proceed without a reference query","Too many documents exceeding model token limits — truncation or error"],"whenToPreferThis":"Choose this endpoint when you need neural cross-encoder reranking to improve precision of retrieved documents in a RAG or search pipeline, especially when you want no API key management (x402 USDC payment handles auth) and want automatic fallback from Cohere to Jina. Prefer it over embedding-only retrieval when you need a second-stage reranker to boost relevance of your top-k candidates.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T18:30:47.678Z","isFirstParty":false}